RNA aptamers to mammalian initiation factor 4G inhibit cap-dependent translation by blocking the formation of initiation factor complexes
Bibliographic record
Abstract
Eukaryotic translation initiation factor 4G (eIF4G) plays a crucial multimodulatory role in mRNA translation and decay by interacting with other translation factors and mRNA-associated proteins. In this study, we isolated eight different RNA aptamers with high affinity to mammalian eIF4G by in vitro RNA selection amplification. Of these, three aptamers (apt3, apt4, and apt5) inhibited the cap-dependent translation of two independent mRNAs in a rabbit reticulocyte lysate system. The cap-independent translation directed by an HCV internal ribosome entry site was not affected. Addition of exogenous eIF4G reversed the aptamer-mediated inhibition of translation. Even though apt3 and apt4 were selected independently, they differ only by two nucleotides. The use of truncated eIF4G variants in binding experiments indicated that apt4 (and probably apt3) bind to both the middle and C-terminal domains of eIF4G, while apt5 binds only to the middle domain of eIF4G. Corresponding to the difference in the binding sites in eIF4G, apt4, but not apt5, hindered eIF4G from binding to eIF4A and eIF3, in a purified protein solution system as well as in a crude lysate system. Therefore, the inhibition of translation by apt4 (and apt3) is due to the inhibition of formation of initiation factor complexes involving eIF4A and eIF3. On the other hand, apt5 had a much weaker affinity to eIF4G than apt4, but inhibited translation much more efficiently by an unknown mechanism. The five additional aptamers have sequences and predicted secondary structures that are largely different from each other and from apt3 through apt5. Therefore, we speculate that these seven sets of aptamers may bind to different regions in eIF4G in different fashions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".